I am having issues in storing the results of auto-correlations:
sysuse sp500.dta
tsset date
corrgram open
di `r(ac10)'
di `r(ac11)'
As you see, the corrgram command opens a table with AC, PAC, Q etc.
I wish to store the data, but somehow I cannot access all the information.
Why can I get data from r(ac10) and not r(ac11)? I mean, the information is already there, can someone enlighten me?
The corrgram command returns certain results such as r(ac1) - r(ac10) as scalars:
. return list
scalars:
r(lags) = 40
r(q10) = 997.7976424554661
r(pac10) = .
r(ac10) = .4660537633851876
r(q9) = 941.2145380745385
r(pac9) = .
r(ac9) = .4926995142415946
r(q8) = 878.2410054272498
r(pac8) = .
r(ac8) = .6798652708950988
r(q7) = 758.8350022301894
r(pac7) = .
r(ac7) = .8497950586730207
r(q6) = 573.0532520717032
r(pac6) = .
r(ac6) = .7058394210650882
r(q5) = 445.4128558881126
r(pac5) = .
r(ac5) = .537862961940051
r(q4) = 371.600563372601
r(pac4) = -.123160137402293
r(ac4) = .5238127059274379
r(q3) = 301.8811184740619
r(pac3) = .0903652372655368
r(ac3) = .5378744937938151
r(q2) = 228.6682359982045
r(pac2) = -.0172170443544806
r(ac2) = .5633576757209979
r(q1) = 148.6802035217271
r(pac1) = .9912569913768637
r(ac1) = .769625068645877
However, it also returns everything as matrices:
matrices:
r(Q) : 1 x 40
r(PAC) : 1 x 4
r(AC) : 1 x 40
You can access what you need from the respective returned matrix e.g. r(Q), r(PAC) or r(AC).
For ac11 specifically:
. display el(r(AC), 1, 11)
.46352669
or
. matrix A = r(AC)
. display A[1,11]
.46352669
To save the returned results directly as a Stata variable with the name ac:
mata: st_store((1::40), st_addvar("double","ac"), colshape(st_matrix("r(AC)"), 1))
. list ac in 1 / 40
+-----------+
| ac |
|-----------|
1. | .76962507 |
2. | .56335768 |
3. | .53787449 |
4. | .52381271 |
5. | .53786296 |
|-----------|
6. | .70583942 |
7. | .84979506 |
8. | .67986527 |
9. | .49269951 |
10. | .46605376 |
|-----------|
11. | .46352669 |
12. | .47980565 |
13. | .62691605 |
14. | .76459033 |
15. | .59986479 |
|-----------|
16. | .43064803 |
17. | .41606848 |
18. | .4143769 |
19. | .42979786 |
20. | .55313291 |
|-----------|
21. | .6518829 |
22. | .50817027 |
23. | .35552032 |
24. | .34330162 |
25. | .34298527 |
|-----------|
26. | .34803055 |
27. | .44354181 |
28. | .52455024 |
29. | .40499719 |
30. | .28776225 |
|-----------|
31. | .2736146 |
32. | .27286332 |
33. | .27667982 |
34. | .34373118 |
35. | .40664714 |
|-----------|
36. | .30633385 |
37. | .21286866 |
38. | .19836486 |
39. | .20569954 |
40. | .20306142 |
+-----------+
I think it is easier to store these as variables rather than messing with the matrices or scalars:
. webuse air2, clear
(TIMESLAB: Airline passengers)
. corrgram air, lags(20)
-1 0 1 -1 0 1
LAG AC PAC Q Prob>Q [Autocorrelation] [Partial Autocor]
-------------------------------------------------------------------------------
1 0.9480 0.9589 132.14 0.0000 |------- |-------
2 0.8756 -0.3298 245.65 0.0000 |------- --|
3 0.8067 0.2018 342.67 0.0000 |------ |-
4 0.7526 0.1450 427.74 0.0000 |------ |-
5 0.7138 0.2585 504.8 0.0000 |----- |--
6 0.6817 -0.0269 575.6 0.0000 |----- |
7 0.6629 0.2043 643.04 0.0000 |----- |-
8 0.6556 0.1561 709.48 0.0000 |----- |-
9 0.6709 0.5686 779.59 0.0000 |----- |----
10 0.7027 0.2926 857.07 0.0000 |----- |--
11 0.7432 0.8402 944.39 0.0000 |----- |------
12 0.7604 0.6127 1036.5 0.0000 |------ |----
13 0.7127 -0.6660 1118 0.0000 |----- -----|
14 0.6463 -0.3846 1185.6 0.0000 |----- ---|
15 0.5859 0.0787 1241.5 0.0000 |---- |
16 0.5380 -0.0266 1289 0.0000 |---- |
17 0.4997 -0.0581 1330.4 0.0000 |--- |
18 0.4687 -0.0435 1367 0.0000 |--- |
19 0.4499 0.2773 1401.1 0.0000 |--- |--
20 0.4416 -0.0405 1434.1 0.0000 |--- |
. ac air , lag(20) gen(ac)
. pac air, lag(20) gen(pac)
. list t ac pac in 1/20, clean noobs
t ac pac
1 .94804734 .95893198
2 .87557484 -.32983096
3 .80668116 .2018249
4 .75262542 .14500798
5 .71376997 .25848232
6 .6817336 -.02690283
7 .66290439 .20433019
8 .65561048 .15607896
9 .67094833 .56860841
10 .70271992 .29256358
11 .74324019 .8402143
12 .76039504 .61268285
13 .71266087 -.66597616
14 .64634228 -.38463943
15 .58592342 .0787466
16 .53795519 -.02663483
17 .49974753 -.05805221
18 .46873401 -.04350748
19 .44987066 .27732556
20 .4416288 -.04046447
